Impedimetric Detection Based on Label-Free Immunoassay Developed for Targeting Spike S1 Protein of SARS-CoV-2

After the COVID-19 pandemic started all over the world, great importance was placed on the development of sensitive and selective bioanalytical assays for the rapid detection of the highly pathogenic SARS-CoV-2 virus causing COVID-19 disease. In this present work, an impedimetric immunosensor was developed and applied for rapid, reliable, sensitive and selective detection of the SARS-CoV-2 S1 protein. To detect the SARS-CoV-2 virus, targeting of the spike S1 protein was achieved herein by using S1 protein-specific capture antibody (Cab-S1) immobilized screen-printed electrode (SPE) in combination with the electrochemical impedance spectroscopy (EIS) technique. With the impedimetric immunosensor, the detection limit for S1 protein in buffer medium was found to be 0.23 ng/mL (equal to 23.92 amol in 8 µL sample) in the linear concentration range of S1 protein from 0.5 to 10 ng/mL. In the artificial saliva medium, it was found to be 0.09 ng/mL (equals to 9.36 amol in 8 µL sample) in the linear concentration range of S1 protein between 0.1 and 1 ng/mL. The selectivity of the impedimetric immunosensor toward S1 protein was tested against influenza hemagglutinin antigen (HA) in the buffer medium as well as in artificial saliva.

Introduction
After the beginning of COVID-19 pandemic, there were significant efforts to develop easy-to-use, fast, inexpensive and accurate diagnostic tests that could provide an advantage against this emerging threat.
The SARS-CoV-2 spike protein has two regions: S1 and S2. As the S1 region of the spike protein interacts with the host cell receptors, it permits the SARS-CoV-2 virus to enter the cell [1][2][3]. The S2 region of the spike protein is responsible for the fusion of the virus with the cell membrane of the host cell [3].
Electrochemical methods provide many advantages, such as competitive sensitivity, cost-effectiveness, rapidity, easy-to-use qualities and suitability for miniaturization, while allowing the point-of-care testing of many inherited and genetic diseases in comparison to conventional methods [16,17].
Electrochemical methods have been successfully and practically applied for the development of electrochemical immunosensors based on different types of electrodes; the screen-printed electrode (SPE), the carbon paste electrode (CPE) and the glassy carbon electrode (GCE) etc. [18][19][20].
Nowadays, SPEs are more preferentially used, due to advantages such as disposability and greater suitability for implementation to portable devices, being able to provide sensitive and precise analysis using a small of sample [12,21,22].
The electrochemical impedance spectroscopy (EIS) technique is used in many fields of electrochemistry, such as electrode kinetics, double-layer studies, solid-phase electrochemistry and bioelectrochemistry. It is a beneficial method for investigating the interface properties on conductive and semiconductor surfaces [23]. The use of this highly sensitive and label-free technique in the development of biosensing strategies is increasing gradually in the examination of numerous types of biochemical interactions (e.g., antigen-antibody, DNA-DNA interactions, drug-DNA interactions, aptamer-based protein, cell, etc.) [24][25][26].
Some earlier studies have been conducted regarding the implementation of EIS technique in the detection of SARS-CoV-2 [6,7,10,[27][28][29][30][31][32][33][34][35][36][37]. For instance, Rahmati et al. [6] modified the surfaces of disposable SPCEs with Cu 2 O nanocubes and immobilized Protein A onto the modified electrode surface. After immobilization of the IgG antibody onto the surface of the modified electrode, the sample containing SARS-CoV-2 spike antigen was added onto the surface of electrode, and impedimetric measurement was conducted accordingly. In the study introduced by Torres et al. [7], angiotensin-converting enzyme 2 (ACE2) solution was added onto the surface of paper-based electrodes during 1.5 h immobilization time. After the immobilization step, SARS-CoV-2 virus detection was explored by EIS technique. Streptavidin-modified boron-doped polycrystalline diamond electrodes were developed for the immobilization of biotin-labeled SARS-CoV-2 S1 antibodies and then applied for impedimetric detection of the SARS-CoV-2 S1 protein [37]. However, the procedure was similar to the most of earlier reports on impedimetric immunosensors, with the authors following a time-consuming procedure for the development of the immunosensor, while using expensive and laborious electrodes.
In the present study, a label-free immunoassay was designed and combined with the impedimetric detection of spike S1 protein, and its applicability to real samples was also demonstrated. Under this objective, S1 protein-specific capture antibody (Cab-S1) was firstly attached onto the electrode surface. After dropping the sample containing spike S1 protein onto the surface, a specific immunoreaction occurred based on the antibodyantigen interaction. The sensitive and selective detection of S1 protein was explored impedimetrically in buffer and artificial saliva medium, as well as the selectivity of the label-free impedimetric immunosensor against Hemagglutinin antigen (HA). The analytical performance of the immunosensor was also reported with regards to its limit of detection (LOD), the reproducibility and the sensitivity.

Chemicals and Apparatus
Detailed information about SARS-CoV-2 spike S1 protein, its specific capture antibody (Cab-S1), hemagglutinin antigen (HA) and bovine serum albumin (BSA) is given in Table S1 of Supplementary Materials. The required information about each of the buffer solutions, as well as the details on the equipment and apparatus is also given in Supplementary Materials.

Procedure
The procedure based on the SARS-CoV-2 S1 protein-specific impedimetric immunosensor was developed through the following steps: (i) activation of the surface of the SPE; (ii) immobilization of Cab-S1 onto the electrode surface; (iii) blocking of the electrode surface; (iv) incubation of S1 protein at the electrode surface, and (v) impedimetric measurement.
Activation of the surface of the SPE: Electrochemical activation of the electrode surface was performed similarly to a previous study [12]. The solution containing 5 mM EDC and 8 mM NHS was prepared in PBS (50 mM, pH 7.40), as reported in earlier literature [38,39]. Chemical activation was carried out by dropping 8 µL of EDC/NHS solution onto the electrode surface, and it was kept for 60 min. After activation of the electrode surface, the electrode was rinsed with PBS (50 mM, pH 7.40) for 10 s. All steps were performed at room temperature unless otherwise stated.
Immobilization of Cab-S1 onto the electrode surface: 1 µg/mL Cab-S1 was prepared in PBS (50 mM, pH 7.40). An amount of 8 µL of Cab-S1 solution was pipetted onto the electrode surface and kept for 1 h. After immobilization of Cab-S1, the electrode was rinsed with PBS (50 mM, pH 7.40) for 10 s.
Blocking of the electrode surface: In order to block the free sites at the electrode surface, BSA was used as a blocking agent. An amount of 0.5 µg/mL BSA solution was prepared using PBS (50 mM, pH 7.40). Then 8 µL of BSA solution was pipetted onto the electrode surface and kept for 30 min. After the blocking step, the electrode was rinsed with PBS (50 mM, pH 7.40) for 10 s.
Incubation of S1 protein at the electrode surface: S1 protein was prepared in its different concentrations using PBS (50 mM, pH 7.40). An amount of 8 µL of S1 protein solution was pipetted onto the electrode surface and incubated for 30 min at 37 • C in a drying oven. After the incubation step, the electrode was rinsed with PBS (50 mM, pH 7.40) for 10 s. The schematic representation of the label-free impedimetric immunosensor specific to spike S1 protein is illustrated in Figure 1. and 8 mM NHS was prepared in PBS (50 mM, pH 7.40), as reported in earlier liter [38,39]. Chemical activation was carried out by dropping 8 µL of EDC/NHS solution the electrode surface, and it was kept for 60 min. After activation of the electrode sur the electrode was rinsed with PBS (50 mM, pH 7.40) for 10 s. All steps were perform room temperature unless otherwise stated.
Immobilization of Cab-S1 onto the electrode surface: 1 µg/mL Cab-S1 was prep in PBS (50 mM, pH 7.40). An amount of 8 µL of Cab-S1 solution was pipetted ont electrode surface and kept for 1 h. After immobilization of Cab-S1, the electrode rinsed with PBS (50 mM, pH 7.40) for 10 s.
Blocking of the electrode surface: In order to block the free sites at the elect surface, BSA was used as a blocking agent. An amount of 0.5 µg/mL BSA solution prepared using PBS (50 mM, pH 7.40). Then 8 µL of BSA solution was pipetted ont electrode surface and kept for 30 min. After the blocking step, the electrode was ri with PBS (50 mM, pH 7.40) for 10 s.
Incubation of S1 protein at the electrode surface: S1 protein was prepared different concentrations using PBS (50 mM, pH 7.40). An amount of 8 µL of S1 pr solution was pipetted onto the electrode surface and incubated for 30 min at 37 °C drying oven. After the incubation step, the electrode was rinsed with PBS (50 mM 7.40) for 10 s. The schematic representation of the label-free impedimetric immunosensor sp to spike S1 protein is illustrated in Figure 1.  The selectivity of label-free immunosensor to S1 protein was analyzed against hemagglutinin antigen (HA) by following the procedure described above.
To demonstrate the applicability of the label-free impedimetric immunosensor to real samples, a batch of experiments was performed in artificial saliva medium. The samples of S1 protein in different concentrations were prepared by using diluted artificial saliva. After following each of these steps in buffer medium as established above, EIS measurements were performed.

Results & Discussion
The characterization of the construction of our immunosensor was carried out using the cyclic voltammetry (CV) technique in the redox probe solution, and accordingly, the results were given in Figure S2 and Table S2.
As shown in Figure S2, a well-defined peak was observed by unmodified screenprinted carbon electrode. A slight decrease in current was observed after chemical activation of the electrode surface with EDC/NHS. Then a decrease in current occurred after Cab-S1 immobilization onto the electrode surface. Due to the steric/conformational restriction at the electrode surface with the barrier effect of protein molecules, inhibition of electron transfer occurred, and thus a decrease in current was observed. This change in current indicates that the antibody was successfully immobilized onto the electrode surface. Then, a decrease in current with the shift in the redox peaks occurred after blocking step and then again following incubation of S1 protein on the electrode surface. An increase in ∆E p was recorded from 113 mV to 132 mV after the blocking step, and similarly, an increase in ∆E p (from 132 mV to 142 mV) was obtained by incubating S1 protein onto the electrode surface. Due to the insulating character of the biological components immobilized onto the electrode surface and the more steric/conformational restrictions of the proteins, the electron transfer was inhibited. Hence, a decrease in current with the shift in the redox peaks was observed, similarly to the results presented in previous studies [6,28,34,40,41].
The effects of different antibody sources upon the response was examined based on the interaction of antibodies with the spike S1 protein. The interaction of antibodyantigen was investigated using antibodies with different sources; e.g., human monoclonal antibody (mAb), rabbit mAb and rabbit polyclonal antibody (pAb), in order to perform more sensitive and specific analysis of the spike S1 protein of SARS-CoV-2. The results are shown in Table S3 of Supplementary Materials. The highest difference ratio (15.39%) was obtained in the procedure by using human mAb as Cab-S1 with the addition of spike S1 protein onto the surfaces of all electrodes. Hence, a human mAb was used as Cab-S1 for the detection of SARS-CoV-2 in our assay, similarly to earlier studies presented by Lien et al. [42] and Nessark et al. [43].
The experimental parameters, including the concentration of Cab-S1 (Table S4) and BSA (Table S5); BSA blocking time (Table S6); antigen incubation time (Table S7) and antigen incubation temperature (Table S8) were examined. The optimum experimental parameters are summarized in Table 1 with the results presented in Figure S3 of Supplementary Materials. Table 1. Optimum conditions of the label-free impedimetric immunosensor developed for the detection of spike S1 protein of SARS-CoV-2.

15-30-60 30
Antigen incubation temperature Room temperature-37 • C 37 • C Next, the analytical performance of the label-free impedimetric immunosensor was explored by following the optimum experimental conditions. The diluted solutions of spike S1 protein were prepared in PBS, and EIS measurements were carried out accordingly (shown in Figure S4).
An increase in average Rct value was recorded in the concentration range of S1 protein varying from 0.5 ng/mL to 10 ng/mL (Figure 2A). The limit of detection (LOD) is estimated by using the method of Miller and Miller [44] with a regression equation and the definition as "y = yB + 3SB" (yB is the signal of blank solution and SB is the standard deviation of the blank solution). definition as "y = yB + 3SB" (yB is the signal of blank solution and SB is the standard deviation of the blank solution).
Based on the calibration graph with a regression equation: = 14.623 + 395.72 ( = 0.99) (shown in Figure 2B), the LOD was estimated as 0.23 ng/mL. The sensitivity of the immunosensor was calculated by the ratio of the slope of the calibration plot (14.623) to the active surface area (0.42 cm 2 ) of the working electrode, and it was found to be 34.82 Ohm mL ng −1 cm −2 .

Figure 2. (A)
Nyquist diagrams showing the data obtained by impedimetric immunosensor for the detection of S1 protein in its concentrations varying from 0.5 to 10 ng/mL prepared in buffer medium. (B) Calibration curve obtained by impedimetric detection of spike S1 protein of SARS-CoV-2 (n = 6). the data obtained by impedimetric immunosensor for the detection of S1 protein in its concentrations varying from 0.5 to 10 ng/mL prepared in buffer medium. (B) Calibration curve obtained by impedimetric detection of spike S1 protein of SARS-CoV-2 (n = 6).
Based on the calibration graph with a regression equation: y = 14.623x + 395.72 (R 2 = 0.99) (shown in Figure 2B), the LOD was estimated as 0.23 ng/mL. The sensitivity of the immunosensor was calculated by the ratio of the slope of the calibration plot (14.623) to the active surface area (0.42 cm 2 ) of the working electrode, and it was found to be 34.82 Ohm mL ng −1 cm −2 .
The repeatability of the impedimetric immunosensor was examined, and the results are given in Table S9. Inter-day relative standard deviation (RSD %) value was calculated by six repetitive measurements at six different concentrations of spike S1 protein of SARS-CoV-2. Accordingly, the RSD value was found to be below 10% in each concentration of S1 protein.
It can be concluded that the impedimetric immunosensor specific to spike S1 protein provides precise and sensitive analysis for the detection of SARS-CoV-2.
Since the diseases COVID-19 and influenza show similar symptoms, such as cough, fever, fatigue and headache, the selectivity studies were explored herein using one of the widely tested biomarkers of influenza, HA antigen. This antigen was preferentially studied in this work, similarly to other interferents used in earlier studies developed for the detection of COVID-19; such as, influenza virus A (H1N1), 2009 influenza virus pH1N1 [4], influenza A and B antigens [6], influenza A viruses [35] (H3N2 Brisbane virus and H1N1 New Caledonia virus), influenza A virus N-protein, and influenza B virus N-protein [45], influenza B, B/Colorado [7], influenza A viruses (H1N1, H5N1, and H3N2) and influenza B [33].
The selectivity studies were performed in the concentrations of 1, 5, 7 and 10 ng/mL of spike S1 protein or HA prepared in buffer medium. An increase in average Rct value was obtained while increasing the concentration of S1 protein, however, the average Rct value remained almost constant while increasing concentration of HA. (Figure 3). Even with a 10-fold increase in HA concentration (1 ng/mL to 10 ng/mL), the average Rct values remained almost constant without a significant change. However, in the presence of S1 protein, an increase in Rct value was observed proportionally to the S1 protein concentration (Figure 3). These results indicate that the impedimetric immunosensor presented a good selectivity toward its target S1 protein in contrast to HA antigen. S1 protein. It can be concluded that the impedimetric immunosensor specific to spike S1 protein provides precise and sensitive analysis for the detection of SARS-CoV-2.
Since the diseases COVID-19 and influenza show similar symptoms, such as cough, fever, fatigue and headache, the selectivity studies were explored herein using one of the widely tested biomarkers of influenza, HA antigen. This antigen was preferentially studied in this work, similarly to other interferents used in earlier studies developed for the detection of COVID-19; such as, influenza virus A (H1N1), 2009 influenza virus pH1N1 [4], influenza A and B antigens [6], influenza A viruses [35] (H3N2 Brisbane virus and H1N1 New Caledonia virus), influenza A virus N-protein, and influenza B virus N-protein [45], influenza B, B/Colorado [7], influenza A viruses (H1N1, H5N1, and H3N2) and influenza B [33].
The selectivity studies were performed in the concentrations of 1, 5, 7 and 10 ng/mL of spike S1 protein or HA prepared in buffer medium. An increase in average Rct value was obtained while increasing the concentration of S1 protein, however, the average Rct value remained almost constant while increasing concentration of HA. (Figure 3). Even with a 10-fold increase in HA concentration (1 ng/mL to 10 ng/mL), the average Rct values remained almost constant without a significant change. However, in the presence of S1 protein, an increase in Rct value was observed proportionally to the S1 protein concentration ( Figure 3). These results indicate that the impedimetric immunosensor presented a good selectivity toward its target S1 protein in contrast to HA antigen. Histograms presenting the data obtained in the selectivity study performed in different concentrations of S1 protein or HA. Gray columns represent full procedure in the presence of spike S1 protein, and green-striped columns represent full procedure in the presence of HA (n = 3).
The implementation of the label-free impedimetric immunosensor specific to spike S1 protein of SARS-CoV-2 to real samples was investigated in the samples prepared by using artificial saliva medium, along with its application in easy and non-invasive analysis of COVID-19.
Since the artificial saliva medium is a complex matrix, it is important to minimize the effects of possible interferents available in artificial saliva medium. There are some reports Figure 3. Histograms presenting the data obtained in the selectivity study performed in different concentrations of S1 protein or HA. Gray columns represent full procedure in the presence of spike S1 protein, and green-striped columns represent full procedure in the presence of HA (n = 3).
The implementation of the label-free impedimetric immunosensor specific to spike S1 protein of SARS-CoV-2 to real samples was investigated in the samples prepared by using artificial saliva medium, along with its application in easy and non-invasive analysis of COVID-19.
Since the artificial saliva medium is a complex matrix, it is important to minimize the effects of possible interferents available in artificial saliva medium. There are some reports in the literature [4,9,46] presenting the application of the immunosensor in undiluted artificial saliva medium as well as in diluted forms of the medium in ratios ranging from 1:5 to 1:100. Accordingly, the effect of different dilution ratio upon the immunosensor response was examined in our study.
The Rct value was measured in the presence of diluted artificial saliva medium; 1:5 and 1:20 respectively as 363.00 ± 22.63 with RSD 6.23% (n = 2) and 364.00 ± 5.66 with RSD 1.55% (n = 2). After incubation of the sample of diluted artificial saliva (1:20) onto the electrode surface, more reproducible results were obtained. The resulting Nyquist diagram is shown in Figure S5.
The difference ratio (%) was calculated according to Equation (S1) given in Supplementary Materials. A higher difference ratio (30.28% increase) was found in the presence of S1 protein prepared in diluted artificial saliva in the ratio of 1:20, in contrast to the one (13.72% increase) prepared in diluted artificial saliva in the ratio of 1:5 ( Figure S5).
The solutions of spike S1 protein were then prepared by using an artificial saliva dilution of 1:20, and accordingly, EIS measurements were performed after following the experimental procedure above. The data are shown in Figure S6.
An increase in average Rct value was recorded in the concentration range of 0.1 ng/mL-1 ng/mL S1 protein prepared in artificial saliva medium ( Figure 4A). Based on the calibration graph with a regression equation: y = 108.31x + 391.08 (R 2 = 0.99) (shown in Figure 4B), the LOD was found to be 0.09 ng/mL, according to the Miller and Miller method [44]. The sensitivity of the immunosensor was also calculated by the ratio of the slope of the calibration plot (108.31) to the active surface area (0.42 cm 2 ) of the working electrode, and it was found to be 257.88 Ohm mL ng −1 cm −2 in artificial saliva medium.  Next, the selectivity of the label-free impedimetric immunosensor was explored in the medium of diluted artificial saliva (1:20). S1 protein or HA was prepared in the concentrations of 0.25, 0.5 and 1 ng/mL in diluted artificial saliva medium (1:20). A gradual increase in the average Rct was observed with increasing concentrations of spike S1 protein, whereas the average Rct remained relatively steady at increasing concentrations of In our study, the concentration range for S1 protein was found to be similar to the concentration range of the antigen obtained in the samples of COVID-19 patients, as investigated in saliva samples by the rRT-PCR technique [11].
Next, the selectivity of the label-free impedimetric immunosensor was explored in the medium of diluted artificial saliva (1:20). S1 protein or HA was prepared in the concentrations of 0.25, 0.5 and 1 ng/mL in diluted artificial saliva medium (1:20). A gradual increase in the average Rct was observed with increasing concentrations of spike S1 protein, whereas the average Rct remained relatively steady at increasing concentrations of HA ( Figure 5). Even in a complex environment, such as artificial saliva, the immunosensor selectively detected the S1 protein prepared in three different concentrations. In addition, more repeatable results were obtained in the presence of S1 protein compared with the results observed with HA. These results indicate that the impedimetric immunosensor presented a good selectivity toward its target S1 protein over HA antigen. Histograms presenting the data obtained in the selectivity study performed on different concentrations of S1 protein or HA prepared in diluted artificial saliva (1:20). Gray columns represent full procedure in the presence of spike S1 protein, and green-striped columns represent full procedure in the presence of HA (n = 3).
A further experiment on the selectivity of the immunosensor was performed on the mixture sample of spike S1 protein and HA (1:1) prepared in diluted artificial saliva (1:20). The resulting Nyquist diagram is shown in Figure S7.
The lower Rct values were measured in the presence of 1 ng/mL HA protein (384.33 ± 44.09 Ohm; RSD 11.47%, n = 3) and compared with those measured in the presence of 1 ng/mL S1 protein and in the mixture sample of S1 protein and HA (1:1) (496. 33 ± 12.22 Ohm with an RSD of 2.46%, n = 3 and 461. 33 ± 30.17 Ohm with an RSD of 6.54%, n = 3, respectively) (shown in Figure 6). Therefore, it can be concluded that our impedimetric immunosensor presents a good selectivity toward its target S1 protein over HA, even in a complex sample matrix, e.g., artificial saliva. Figure 5. Histograms presenting the data obtained in the selectivity study performed on different concentrations of S1 protein or HA prepared in diluted artificial saliva (1:20). Gray columns represent full procedure in the presence of spike S1 protein, and green-striped columns represent full procedure in the presence of HA (n = 3).
A further experiment on the selectivity of the immunosensor was performed on the mixture sample of spike S1 protein and HA (1:1) prepared in diluted artificial saliva (1:20). The resulting Nyquist diagram is shown in Figure S7.
The lower Rct values were measured in the presence of 1 ng/mL HA protein (384.33 ± 44.09 Ohm; RSD 11.47%, n = 3) and compared with those measured in the presence of 1 ng/mL S1 protein and in the mixture sample of S1 protein and HA (1:1) (496.33 ± 12.22 Ohm with an RSD of 2.46%, n = 3 and 461.33 ± 30.17 Ohm with an RSD of 6.54%, n = 3, respectively) (shown in Figure 6). Therefore, it can be concluded that our impedimetric immunosensor presents a good selectivity toward its target S1 protein over HA, even in a complex sample matrix, e.g., artificial saliva.
The lower Rct values were measured in the presence of 1 ng/mL HA protein (384.33 ± 44.09 Ohm; RSD 11.47%, n = 3) and compared with those measured in the presence of 1 ng/mL S1 protein and in the mixture sample of S1 protein and HA (1:1) (496. 33 ± 12.22 Ohm with an RSD of 2.46%, n = 3 and 461.33 ± 30.17 Ohm with an RSD of 6.54%, n = 3, respectively) (shown in Figure 6). Therefore, it can be concluded that our impedimetric immunosensor presents a good selectivity toward its target S1 protein over HA, even in a complex sample matrix, e.g., artificial saliva. Figure 6. Histograms presenting the data obtained in the selectivity study performed with 1 ng/mL S1 protein, 1 ng/mL HA and the mixture sample containing 1 ng/mL S1 protein and 1 ng/mL HA prepared in diluted artificial saliva (1:20) (n = 3). Figure 6. Histograms presenting the data obtained in the selectivity study performed with 1 ng/mL S1 protein, 1 ng/mL HA and the mixture sample containing 1 ng/mL S1 protein and 1 ng/mL HA prepared in diluted artificial saliva (1:20) (n = 3).
In Table 2, an overview of earlier studies presenting impedimetric immunosensors developed for the detection of COVID-19, including this present study, is summarized. The impedimetric immunosensor based on the label-free immunoassay developed herein provides numerous advantages, allowing analysis with a small sample treatment (8 µL) while showing results within a short time (6 min). In addition, there is no need surface modification applied by using metallic nanoparticles or conductive materials in this study in contrast to some of the studies given in Table 2.  SARS-CoV-2 spike S1 protein (S1 protein) Anti-SARS-CoV-2 S1 antibody There have been many reports in the literature presenting the detection of SARS-CoV-2 virus by different procedures in combination with specific bioreceptors, such as spike protein (S) and nucleocapsid protein (N) [5,47,48]. In addition to the studies targeting spike protein [4,6,7,10,27,49,50], some studies focusing on the detection of S1 subunits [12,51,52] are also presented. The detection of the SARS-CoV-2 virus using combinations of electrochemical techniques, such as voltametric [4,[47][48][49]51,53,54], amperometric [5,9,52] and impedimetric [6,7,10,27,55] techniques, was explored for the determination of different bioreceptors of SARS-CoV-2. In comparison to previous studies reporting on the development of different techniques [8,[56][57][58][59], the advantages of our label-free impedimetric immunosensor are listed as the simple preparation procedure with short preparation time (i.e., 3 h) and rapid analysis (only 6 min). Moreover, no surface modification using nanomaterials, such as graphene [8,56], graphene oxide [57] or gold nanoparticles [57][58][59], was applied in our study. In contrast to optical detection of SARS-CoV-2 [59,60], our assay is easy to apply without requiring any extra labels (such as fluorescent dye, peptide etc.). Moreover, a lower detection limit was achieved herein, in contrast to the studies of Zhu and Zhou [59], Moncayo et al. [61] and Liu et al. [62].
In contrast to earlier work [5], there is no need to use a secondary antibody in applying the label-free immunoassay, since our assay was mainly based on direct interaction of the antibody with its target without applying any extra intermediaries. Moreover, no surface modification using other molecules such as protein A [6] or biotin [37] on the electrode surface was applied in our study. Overall, the surface treatment/functionalization of the immunosensor was achieved herein straightforwardly and faster than for previous approaches using the indium tin oxide (ITO) electrode [10,28] and the boron-doped polycrystalline diamond electrode [37].

Conclusions
The impedimetric immunosensor based on the label-free immunoassay for rapid and sensitive detection of the spike S1 protein of SARS-CoV-2 was introduced for the first time in this study. Under optimized conditions, the detection limit was found to be 0.23 ng/mL (equal to 23.92 amol in 8 µL sample) in the linear concentration range of 0.5-10 ng/mL S1 protein in buffer medium. More sensitive results with a lower detection limit (i.e., 0.09 ng/mL, equal to 9.36 amol in 8 µL sample) were achieved in artificial saliva medium with linear concentration range of spike S1 protein from 0.1 to 1 ng/mL. In the selectivity study performed in the artificial saliva medium, the impedimetric immunosensor presented a highly selective response toward its target spike S1 protein of SARS-CoV-2 over influenza hemagglutinin antigen (HA).
In the present work, lower DL values were achieved for electrochemical detection of SARS-CoV-2 in contrast to earlier studies performed by EIS technique [29,30,32,35], voltammetric methods in combination with labeling of alkaline phosphatase enzyme [4], or using a ferri/ferrocyanide indicator [51]. By comparison earlier studies [6,7,10,[27][28][29]31,33,36,37], the procedure followed from the preparation of the immunosensor up to measurement of the response in the detection of S1 protein was completed in 3 h, while the impedimetric measurement was performed within only 6 min.
The developed impedimetric immunosensor is disposable, easy to use and cost effective, and does not require trained personnel, thus having significant advantages over traditional analysis methods while allowing individuals to perform tests on their own.
The importance of widespread testing in the COVID-19 pandemic has been noted by many authorities. In addition, there are portable biosensors reported in the literature [7,33] that have been implemented to real samples for the impedimetric detection of COVID-19. In this context, it can be concluded that our impedimetric immunosensor presents a great potential for the development of point-of-care testing.
In conclusion, an impedimetric immunosensor specific to the spike S1 protein of SARS-CoV-2 was developed successfully in our study, and provides a sensitive, selective, fast and precise analysis of S1 protein based on label-free immunoassay. Additionally, our immunoassay procedure in combination with the impedimetric technique could be easily adaptable for the further development of a portable point-of-care test system that may be used in possible pandemics in the future.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/diagnostics12081992/s1, Table S1. The information about antibodies and proteins used in this study. Table S2. The average values of anodic current (I a ) and cathodic current (I c ) with anodic/cathodic charge transfer values (Q a/ Q c ) with the values of ∆Ep measured in redox probe by using CV in combination with each of electrodes; SPE, SPE/EDC-NHS, SPE/EDC-NHS/Cab-S1, SPE/EDC-NHS/Cab-S1/BSA and SPE/EDC-NHS/Cab-S1/BSA/S1 Protein. Table S3. The average Rct value with the difference ratio (%) obtained before and after blocking step in experimental procedures by using human monoclonal, rabbit monoclonal and rabbit polyclonal capture antibodies as Cab-S1. Table S4. Average Rct values with the difference ratio (%) at immunosensor response in the presence of Cab-S1, BSA and S1 protein at different Cab-S1 concentrations. Table S5. Average Rct values with the difference ratio (%) at immunosensor response in the presence of Cab-S1, BSA and S1 protein at different BSA concentrations. Table S6. Average Rct values with the difference ratio (%) at immunosensor response in the presence of Cab-S1, BSA and S1 protein at different BSA blocking times. Table S7. Average Rct values with the difference ratio (%) at immunosensor response in the presence of Cab-S1, BSA and S1 protein at different S1 protein incubation times. Table S8. Average Rct values with the difference ratio (%) at immunosensor response in the presence of Cab-S1, BSA and S1 protein at different S1 protein incubation temperatures. Table S9. The average Rct values (n = 6) with RSD (%) obtained in presence of S1 protein in different concentrations. Figure S1. Images of the immunosensor with test setup. (1) Top view of the test setup, (2) side view of the test setup. Figure S2. Cyclic voltammograms of SPE, SPE/EDC-NHS, SPE/EDC-NHS/Cab-S1, SPE/EDC-NHS/Cab-S1/BSA and SPE/EDC-NHS/Cab-S1/BSA/S1 Protein measured in 5 mM [Fe(CN) 6 ] 3−/4− containing 0.1 M KCl by following experimental conditions: 5/8 mM EDC/NHS, 1 µg/mL Cab-S1, 10 µg/mL BSA and 1 µg/mL S1 protein and the potential range between −0.5 V and +1.0 V with a scan rate: 50 mV/s. Figure S3. The effect of each experimental parameters upon to the response of impedimetric immunosensor: (A) Cab-S1 concentration, (B) BSA concentration, (C) BSA blocking time, (D) S1 protein incubation time, (E) S1 protein incubation temperature. White columns represent after the immobilization of Cab-S1, blue columns represent after the blocking with BSA, green columns represent after the incubation of S1 protein. Figure S4. Line graph representing the average Rct values (n = 3) in the concentration range of S1 protein in buffer medium. Figure S5. Nyquist diagrams obtained in the presence of S1 protein prepared in the artificial saliva sample diluted in various ratios. (a) 1:20 diluted, (b) 1:5 diluted artificial saliva medium (control experiment), 0.5 ng/mL S1 protein prepared in (c) 1:5 diluted, (d) 1:20 diluted artificial saliva medium. Figure S6. Line graph representing the average Rct values (n = 3) in the concentration range of S1 protein in artificial saliva medium. Figure S7. Nyquist diagrams obtained in the selectivity study performed with (a) 1 ng/mL S1 protein, (b) 1 ng/mL HA and (c) the mixture of 1 ng/mL S1 protein and 1 ng/mL HA prepared in 1:20 artificial saliva medium (n = 3). References [63][64][65][66][67]

Data Availability Statement:
The data presented in this study are available within the article. Other data that support the findings of this study are available upon request from the corresponding author as well as co-authors.


s2fieldsofstudy: Biology Medicine

text:
Chimeric antigen receptor T cells applied to solid tumors

Chimeric antigen receptor T cell (CAR-T) therapy is novel tumor immunotherapy that enables autologous T to express synthetic receptors to specifically recognize the surface tumor-associated antigens for exerting subsequent antitumor effects, and eliminating the resistance, metastases and recurrence of cancer. Although CAR T cells have exhibited success in eradicating hematologic malignancies, their applications to solid tumors has not yet been achieved due to obstacles such as the immune-suppressor tumor microenvironment and lack of tumor specific target antigens. In this review, we presented advancements in the development of CAR T cell therapy in solid tumors, and offered a brief summary of the challenges, as well as novel engineering and pharmaceutical interventions to overcome these barriers. Looking forward, we discussed the latest studies which are expected to reach the clinicals in the next few years, including CRISPR screens-based CAR modification and CAR T cells driven from progenitor-like T cells. Collectively, this review may inspire researchers and clinicians to develop clinical available strategies of CAR T cell therapies in solid tumor.

effectively treated by optimized chemo-or radiotherapy. Nevertheless, there is still room for improvement in cancer treatment due to the low survival rate caused by the high metastatic and relapse probability of some cancer subtypes and the excessive side effects of current therapies (2)(3)(4). There is ample evidence to support the critical role of the immune system in controlling and eradicating cancer, especially lymphocytes including natural killer (NK) cells that destroy compromised host cells in innate immunity, T cells involved in cell-mediated cytotoxic immunity, and B cells that participate in antibodydriven immunity (5,6).
With the developments of biochemistry engineering and the deepening understanding of anti-tumor immunity mechanisms within the past few years, many advances have been made in the field of cancer immunotherapy. Cancer immunotherapy works by stimulating the immune system to improve pre-existing immunogenicity (e. g., cancer vaccines and adoptive cell therapy) or by neutralizing tumor-mediated immunosuppression (e. g., immune checkpoint blockade). One of the most successful immunotherapies so far is monoclonal antibodies (mAbs), which has been employed to enhance patients' existing immune responses to cancer. There are over 100 mAbs approved by FDA for treating many diseases including several kinds of hematologic malignancies and solid tumors (7). These mAbs mainly induce tumor cell death through blocking the growth factor receptor signaling, and through engaging the antibody-dependent cellular phagocytosis (ADCP), complement-dependent cytotoxicity (CDC), or antibody-dependent cellular cytotoxicity (ADCC) (8).Among these mAbs, rituximab mainly acts through ADCC and CDC, was approved for treating Non-Hodgkin's Lymphoma since 1997 (9). Recently, FDA approved rituximab in combination with chemotherapy to treat previously untreated pediatric patients (6 months to 18 years) with advanced stage of CD20positive diffuse large B-cell lymphoma, Burkitt lymphoma, Burkitt-like lymphoma, or mature B-cell acute leukemia. At the interim analysis, the efficacy of rituximab was proved by the increased event-free survival events and decreased death events in the group receiving rituximab combinatory therapy (10). Inspired by the successful application of mAbs, other antibody formats such as bispecific antibodies and antibody derivatives have now been widely studied as alternative therapeutic agents for cancers (8).
Another example is immune checkpoint blockade (ICB), which has become the most popular strategy of cancer immunotherapy. Under normal conditions, the binding of inhibitory receptors to their ligands leads to the reduced T cell activation, giving rise to a counter-regulatory pathway during physiological T cell activation. Tumor cells utilize this counterregulatory mechanism by activating inhibitory receptors such as CTLA-4 or PD-1 to deliver an inhibitory signal to T cells in order to escape immune elimination. However, treatment with ICB is able to downregulate this immune inhibitory function and shift the immune system balance toward T cell activation. Beginning with the approval of ipilimumab for treatment of melanoma in 2011, seven additional ICBs have been approved by the FDA for a broad range of different cancer indications (11). By combining anticancer drugs with PD-1 antibodies such as Nivolumab and Pembrolizumab, up to 41% of disease control rate was observed in metastatic triple-negative breast cancer (12). Therefore, the PD1/PDL1 pathway is now recognized as one of the most important checkpoints for immune responses, and PD1/PDL1-blckades alone or in combination with other therapies have become the first line treatment standard in many different cancers such as TNBC and metastatic melanoma (11).

Chimeric antigen receptor T cells
Adoptive T cell therapy (ATC) is another important type of cancer immunotherapy. Traditional ATCs rely on endogenous T c e l l r e p e r t o i r e s w h i c h o n l y r e c o g n i z e t h e m a j o r histocompatibility complex (MHC) molecules-presented antigens, and require co-stimulation of CD28 for activation ( Figure 1A). While the genetically modified T cells can express CAR genes to recognize any surface antigen with high affinity independently of MHC molecules. During the manufacture of CAR T cells, leukocytes are generally harvested from patient's blood via leukapheresis and enriched by counterflow centrifugal elutriation (15). The enriched T cells are then activated by stimulating antibodies in the presence of cytokines such as interleukin-2 (IL-2) IL-7, and IL- 15 (16). What makes CAR T cells different from the traditional ATCs is the CAR construct, which is introduced into these enriched T cells after the activation step. A designed CAR construct encoding region is typically inserted into retroviral or lentiviral vectors and integrated into the T cell genome through transduction (17). After this, T cells are incubated in bioreactors for several days to express the CAR construct and then concentrated using a cell washer before infusion back into patients (18).
The first-generation of CARs were composed of the extracellular mAbs-derived variable domains and intracellular CD3z TCR-signaling chains, exhibiting the ability to recognize defined antigens and leading subsequent T cell activation, specific lysis, and cytokine release (19). However, due to the absence of co-stimulation domain, first-generation of CARs exhibited poor expansion and persistence, therefore had little efficacy in clinical trials (20). The second-generation of CAR T cells are regarded as the most mature generation in current clinical trials, and are composed of an extracellular single-chain variable fragment (scFv), a transmembrane spacer, and an intracellular co-stimulatory signaling domain followed by the intracellular region of CD3. The widely used co-stimulatory signaling domain such as CD3z plus 4-1BB or CD28 signaling domains could induce T cell expansion and longer persistence (21,22). The extracellular scFv is typically derived from the variable light (V L ) and variable heavy (V H ) regions of a mousederived monoclonal antibody against target tumor antigens (23). The spacer/hinger domain links the scFv to the transmembrane region that across the cell membrane lipid bilayer (24) and steers the scFv domain to bind its cognate antigen through the flexibility of the hinger. Once the scFv portion recognizes and binds a tumor antigen, the intracellular 4-1BB or CD28 costimulatory domain and CD3z signal to the intracellular downstream pathway. The phosphorylated immunoreceptor tyrosine-based activation motif (ITAM) in CD3z domains then recruits the tyrosine kinase z-associated protein ZAP70, and leads to the downstream activation of NFAT, NF-kB, and AP-1 transcription factor families (25, 26) ( Figure 1B). After that, activated T cells release perforin to punch holes at tumor cell membranes for the entry of cytotoxins and granzyme B to activate the apoptosis-related caspase cascades to initiate cell death. Currently, CAR structure has developed more and more complex forms. Various co-stimulatory domains beyond 4-1BB and CD28 (e. g., OX40, CD27, and ICOS) and alternative extracellular chain design (e.g., nanobodies derived from the variable domain of heavy chain-only antibodies can have comparable binding ability, specificity, and stability to scFv domain, and prevent undesired immune reactions against the linkers within scFv domain) have become the focus of clinical research (27). Moreover, the third-generation CAR T cells combines two co-stimulation domains in one CAR construct to enhance CAR T cells potency. The fourth-generation CAR T cells are additionally modified with an expression cassette containing a transgenic protein such as cytokine IL-12 to activate local immune reaction. They were generated to enhance the antitumor activity for the treatment of solid tumors and provide great potent in future CAR designs (28,29).
After the first B cell leukemia patients received the secondgeneration of CD19-targeted CAR T cells and exhibited profound and lasting positive responses (20), several clinical studies also demonstrated the remarkable success of the secondgeneration CAR T cells in treating hematologic cancers. Among them, CAR T cells targeting the B lymphocyte antigen CD19 (Novartis's tisagenlecleucel) showed exceptional success with a 83% overall remission rate in 63 patients with relapsed or refractory B cell precursor ALL (acute lymphoblastic leukemia) and received U.S. Food and Drug Administration (FDA) approval for the treatment of ALL, marking a historic first approval for CAR T cell therapy (30). Apart from four approved CD19-targeted CAR T cell therapies including lisocabtagene maraleucel (Breyanzi ® ), tisagenlecleucel (Kymriah ® ), axicabtagene ciloleucel (Yescarta ® ), and brexucabtagene autoleucel (Tecartus ® ), the first BCMAdirected CAR T cells idecabtagene vicleucel (Abecma ® ) was approved by the FDA for multiple myeloma on March 26, 2021 based on a 72% overall response rate and a 28% stringent complete response rate from a phase 2 KarMMa trial involving 127 patients with relapsed or refractory multiple myeloma (31). Recently, the FDA approved another BCMA-CAR T cells product ciltacabtagene autoleucel (CARVYKTI ® ) for the treatment of adult patients with relapsed or refractory multiple myeloma after four or more prior lines of therapy, with an overall response rate of 97.9% in efficacy evaluation (32,33). Given such effectiveness showed in these cases, CAR T cells are expected to become the most popular method of treating B cell A B FIGURE 1 Schematic of TCR and CAR recognition and activation. (A) TCR is a heterodimer (one a and one b chain) connected by disulfide bonds that is expressed in complex with intracellular CD3 molecules (g, d, z, and e). T cells are activated after TCR-recognizing peptides are presented by MHC molecules and co-stimulation of CD28 through B7 ligand. (B) CAR independently recognizes surface antigens with high affinity, unconstrained from MHC and co-stimulatory molecule expression on target cancer cells. The extracellular antigen-specific scFv is typically generated from connected V H and V L chains from mAbs against target antigens. Various hinges and transmembrane domains are employed to link scFv and intracellular signaling molecules, which are the co-stimulatory domain (4-1BB/CD28) and CD3z chain in second-generation CARs. CAR T cells are activated to release perforin, granzyme, and several kinds of cytokines after scFv recognition with surface antigens such as CD19 and from signaling through CD3e-associated recruitment and the phosphorylation (P) of ZAP70 (13,14). Blue arrow indicates the upregulation and activation of pathways. Black arrow indicates the molecules movement.
malignancies, and to have similar effects in treating other cancers such as solid tumors. Unfortunately, the current clinical results of CAR T cells in solid tumors are not as ideal as in hematologic cancers. In a study of 11 patients with EGFR-expressing advanced (>50% expression) relapsed/refractory nonsmall-cell lung cancer who received the EGFR-targeted CAR-T cells treatment, only 2 patients obtained partial responses (34). Nevertheless, this study is still one of the most positive trails for CAR T cell therapy in solid tumors. The reason for the different effectiveness of CAR T cell therapy in treating solid tumors and hematologic cancers is complex and has not been fully understood. In this review, we discussed the general factors affecting the efficacy and safety of CAR T cell therapy and some unique key barriers be confronted with in the treatment of solid tumors. Furthermore, we proposed possible solutions based on recent developments in CAR T cell therapies.

Limitation and recent advances in CAR T cell therapies for solid tumors
The compelling success of CAR T cell therapy in treating hematologic malignancies has encouraged its development in solid tumors. Currently, there are more than 30 ongoing phase I or phase I/II clinical trials for CAR T cells treating several kinds of solid tumors (Table 1). For example, an anti-HER2 CAR T cells were validated to be effective at targeting HER2 + cancer in preclinical studies and are now being evaluated in a phase I/II clinical trial for treating HER2 + cancers including breast,  (42). However, many factors that are absent in hematologic malignancies, like trafficking obstacles and immunosuppressive environment, make CAR T cell therapy difficult to achieve sufficient treatment efficacy for solid tumors.
In treating solid tumors, CAR T cell therapy has to face not only several similar challenges observed in hematologic malignancies, such as T cell exhaustion and CARs-related toxicity, but also many other barriers. For example, identifying tumor-specific antigens that are highly and uniformly expressed on solid tumors is considered to be the most challenging factor in CAR T cell design for treating solid tumors. Unlike the treatment of hematologic malignancies where the CD19-CAR T cells recognize the CD19 + tumor cells in the blood, CAR T cells must travel from the blood into solid tumor sites and infiltrate the stromal elements of the solid tumors. Even after successful infiltration, the tumor microenvironment (TME) of solid tumors often prevents the effective anti-tumor immune response from CAR T cells.

CAR T cell expansion and exhaustion
Although the high degree of personalization makes it difficult to compare each approved CAR T cell product, clinical studies have shown that T cell expansion, persistence and memory phenotype are the key factors in the elimination of the cancer, whether in hematologic malignancies or solid tumors. Observed in first-generation CAR T cells, rapid CAR T cell exhaustion became the most significant and the first recognized factor that reduces CAR T cell efficacy (20). The enhanced expansion and persistence of second-generation CAR T cells provided evidence for the critical effect of co-stimulatory domains in CAR constructs (43). CAR T cells constructed with CD28 generally exhibit a more effector-like memory phenotype and undergo a more rapid expansion and subsequent decline, whereas 4-1BB CAR T cells have a more central memory phenotype and exhibit slower expansion but longer persistence (44) as 4-1BB co-stimulation signaling activates both glycolytic metabolism and fatty acid metabolism which enhance the cell cycle progression (45). Hence, 4-1BB-based CAR T cells are considered as a better option in CAR design to prevent CAR T cell exhaustion. However, when targeting tumor cells with low antigen density, 4-1BB-based CAR T cells sometimes fail to be activated, whereas this is not the case of CD28-based CAR T cells (46). Apart from 4-1BB and CD28 based CAR design, the combinatory design of co-stimulation domain in thirdgeneration CAR T cells also works well to prevent T cell exhaustion. Zhou et al. showed superior efficiency of anti-CD19 CAR T cells that incorporate CD27-CD28 in a phase I trial treating B cell non-Hodgkin lymphomas. The overall response rate for the 21 patients was 67% with 43% of patients achieving a complete response (47). Additionally, Guedan et al. also explored ICOS in combination with 4-1BB co-stimulation, and found that this could effectively prevent the exhaustion of CAR T cells, and exhibit increased efficacy compared to secondgeneration CAR T cells in a mouse solid tumor model (48).
The expansion and exhaustion of CAR T cells also rely on the T cell subsets in the infused product, which determines the memory phenotype of the T cells. During current manufacture of CAR T cells, heterogeneous T cells consisting of both CD4 + and CD8 + T cells displaying an early memory phenotypes are used without subset separation. Researchers hypothesized that CAR T cells generated using certain subset of T cells such as central memory phenotype T cells (49), memory stem T cells (50), CD26 high T cells (51), and virus specific memory T cells (52) may exhibit greater replicative potential. Strong expansion potential and target-specific cytotoxicity have been documented in a T cell product composed of 50% central memory T cells and 46% stem cell-like memory T cells (50). Nevertheless, due to the low composition percentage of these subtypes in T cell populations, which makes them hard to separate from patients' peripheral blood mononuclear cells (PBMC) and concentrate to desired levels, it is difficult to commercialize such CAR subtype T cells. Even though some methods to isolate defined T cell subsets under good manufacturing (GMP) conditions have been developed (53), the requirement for large-scale continuous and quantitative purification with GMP-quality reagents are still the great challenge to construct CAR T cells from these rarer subsets.
In addition, T cells can be modified or impacted by supplementary reagents during the ex vivo manufacture process to prevent their exhaustion after infusion. Shifrut et al. developed a CRISPR-based method coupled with single-cell RNA sequencing to identify key regulators of stimulation responses in T cells. The disruption of genes such as suppressors of cytokine signaling 1 (SOCS1), Tet methyl cytosine dioxygenase 2 (TET2), and transcription elongation factor B polypeptide 2 (TCEB2) have been shown to enhance T cell expansion and tumor-specific cytotoxicity (54). Modification of endogenous promoters and epigenetic can also be utilized to prevent T cell exhaustion (55). Wang et al. suggested that as a DNA methyltransferase inhibitor, decitabine, can be employed to reverse the DNA methylation that contributes to CAR T cell exhaustion (56). Moreover, the exogenous cytokines or pharmacological inhibitors used during the manufacturing process contribute to the exhaustion of CAR T cells. Zhou et al. compared the CAR T cells expanded from PBMCs using different cytokines and indicated that IL-2 expanded CAR T cells are more exhausted compared to IL-7/ 15-expanded ones (57). Watanabe et al. summarized that coculturing of T cells with some pharmacological inhibitors (e.g., the IKT inhibitor ibrutinib, BET inhibitor JQ-1) can specifically suppress T cell exhaustion (58). All of these studies suggested that T cells modifications and cytokines/pharmacal supplementation may significantly improve the efficacy of the final infusion product.

Cytokine release syndrome and neurotoxicity
Despite the extreme potency of CAR T cell therapy, it has significant potential toxic side effects including cytokine release syndrome (CRS) and neurotoxicity in both hematologic malignancies and solid tumors. The manifestation spectrum of CRS ranges from fever, hypotension, to respiratory insufficiency (59), and neurotoxicity includes delirium, epileptic seizures, and even fatal cerebral edema (60). Both CRS and neurotoxicity appear frequently in clinical treatment and have been observed within CD19-specific, BCMA-specific T cells and EGFRvIII-CAR T cells during glioblastoma treatment (61). Additionally, CRS is associated with high circulating levels of several cytokines including granulocytemacrophage colony-stimulating factor (GM-CSF), tumor necrosis factor (TNF), and interferon-g (IFNg) that are secreted by the activated CAR T cells. Theses cytokines then induce other immune cells, such as macrophages to release more cytokines (IL-1, IL-6), and create an inflammation loop called a cytokine storm (62) (Figure 2).
Although neurotoxicity is highly associated with systemic cytokine levels and CRS in clinical settings, the mechanisms involved are still not fully understood. Parker et al. found by single cell sequencing that some brain mural cells expressed CD19 on the cell surface. Hence, they hypothesized that neurotoxicity is probably caused by CD19-based CAR T cell activity against these cells (63). This may be an explanation for the off-target toxicity of CAR T cells, but can't explain the neurotoxicity observed in patients treated with BCMA-specific T cells (64). Another generally accepted hypothesis is that inflammatory cytokines may activate endothelial cells in the brain vasculature, increasing vascular permeability to soluble mediators, CAR T cells, and other lymphocytes. The increased trafficking of cytokines and lymphocytes into central nervous system parenchyma then leads to focal edema and neurotoxicity (65) (Figure 2).
In most clinical cases, CRS and neurotoxicity are treatable and reversible. The most commonly used solution is to break the cytokine feedback loop by blocking the IL-6 receptor with mAb tocilizumab or inhibiting macrophage inflammatory activation to secrete IL-6 by using a-methyltyrosine (metyrosine). Other mAbs targeting GM-CSF (lenzilumab), IL-1 receptor (anakinra) and catecholamines (atrial natriuretic peptide), which induce CRS through a self-augmenting loop, are also employed to break the feedback loop in clinical settings (66,67). Interventions to manage toxicity beyond the direct interruption of the cytokine loop are also under investigation, such as genetically altering CAR T cells to knock out the GM-CSF expressing gene (68), or introducing a suicide gene such as the inducible caspase-9 enzyme gene to get rid of CAR T cells within a short time after infusion (69). Molecular mechanism of CAR T cell-induced CRS and neurotoxicity. After recognizing tumor specific antigens, activated CAR T cells secret GM-CSF, TNF, and IFNg, leading to the release of IL-1 and IL-6 by macrophages and other immune cells, which in turn activates macrophages to form a cytokine feedback loop. The GM-CSF and IL-6 may activate endothelium cells in the brain vasculature to increase its permeability. Blue arrow indicates the upregulation and activation of pathways. Black arrow indicates the molecules movement.

Antigen specificity
The primary reason for the success of CD19-based CAR design in eradicating hematologic malignancies is that CD19 is highly expressed on virtually all acute lymphoblastic leukemia cells, while other cells that express CD19 (B cells) are relatively discardable with the support of intravenous immunoglobulin (70). Despite the fact that BCMA-or CD22-targeted CAR T cells also exhibit tremendous anti-tumor activity in multiple myeloma and acute lymphoblastic leukemia (31,71), all these target antigens are highly restricted to the B cell lineage. The ideal antigens in solid tumors should be selectively expressed at high level on all the tumor cells, but at a very low level or not at all on the surface of important normal tissues in order to improve safety. One study showed fatal toxicity shortly after the infusion of ERBB2/HER2-(a member of human epidermal growth factor receptor frequently overexpressed in many cancers) targeted CAR T cells, which was caused by the recognition and killing of ERBB2-positive cells expressed at low density on the lung endothelium and epithelium (72).
To prevent such on-target off-tumor toxicity, tumor-specific antigens that are only found in cancer cells are considered to be the ideal targets. Hence, CAR T cells targeting EGFR variant 3 (EGFRvIII), which is only expressed on malignant tumor cells (mostly glioblastomas), showed significant efficacy in treating mouse models of glioblastomas (73) and exhibited in vivo safety based on the current result of a phase I study at the University of Pennsylvania (NCT02209376) (61, 74). Aberrant Tn glycopeptides such as the Tn-glycosylated form of MUC1 and Tn-glycosylated podoplanin are another type of tumor-specific antigen that has attracted research interests recently. In particular, COSMC mutation observed in ovarian cancer, leukemia, breast cancer, sarcoma, and neuroblastoma leads to the Tn galactosylation of many surface peptides and therefore provides numerous potential targets for CAR T cell design (75). Posey et al. demonstrated the target-specific cytotoxicity of anti-Tn-MUC1 CAR T cells in xenograft models of leukemia and pancreatic cancer, and further proposed Tn glycosylated antigens as a novel class of targets (76).
Due to lack of more cancer-specific targets, most ongoing clinical trials of CAR T cell therapies for solid tumors continue to target tumor-associated antigens (TAAs) that are overexpressed in tumor cells but still expressed at low levels in normal tissues. One of these antigens is mesothelin (MSLN), which is a glycoprotein overexpressed in mesothelioma, ovarian, and pancreatic carcinomas but low expressed on the surface of peritoneal, pleural, and pericardial cells, has become an attractive target for CAR T cell therapy. One recent study has shown that MSLN-CAR T cells significantly decreased the MSLN + tumor size in mouse models of colorectal and breast cancer (77). Initial results from a phase I clinical trial also suggest the safety and antitumor activity of MSLN-targeted CAR T cells (78).
Despite the safety of this approach demonstrated in several clinical trials, the toxic potential of TAA-targeted CAR T cells should always be monitored carefully when changing any component of CAR T cells.
Richman et al. demonstrated lethal CNS toxicity induced by high-affinity GD2-targeted CAR T cells, which had not presented in previous GD2-targeted CAR T cells trials, and is possibly caused by excessive CAR T cells infiltration and proliferation within the brain (79). Consequently, it is critical to understand the expression levels of TAA in normal tissue in order to predict potential toxicity of TAA-targeted CAR T cells.
To help with this, RNA-sequencing, microarrays, and immunohistochemistry are typically employed to detect certain antigens and analyze their expression levels. However, these technologies may underestimate the antigens expressed by very rare but critically important cells, or may fail to distinguish if expressed genes are derived from tested tissues or infiltrating cells (80). Single-cell RNA sequencing is a new technology that provides the expression profiles of individual cells and thus is able to distinguish target cells from infiltrating cells and other noncritical cells, enabling researchers to predict the toxic potential of novel TAA-targeted CAR T cells more effectively (81).
Additionally, combinatorial antigen targeting is another novel approach developed for enhancing the specificity of TAA-targeted CAR T cells. Wikie et al. designed T cells coexpressing ERBB2-and MUC1-specific CAR that signals using CD3z and CD28 intracellular domains respectively and found that T cells targeting combinatorial antigens can only be fully activated in the presence of both antigens (82) ( Figure 3A). A synthetic Notch receptor system has also been described in a combinatorically activated T cell. Recognized antigen firstly induces the transcription and expression of a CAR molecule for a second antigen, ensuring T cell activation only occurs in the presence of dual tumor antigens (83) ( Figure 3B). Recently, combinatorial antigen targeting strategies were also considered in more advanced CAR designs, such as avidity-controlled CAR (84) and Adapter-CAR (85) to specifically eliminate tumors and protect essential tissues based on complex antigen expression profiles.
Neoantigens are caused by nonsynonymous mutations (NSM) in tumor of certain patients and are considered to be novel "tumor specific antigens" (86). Thus neoantigen-based immunotherapies have the potential to control tumors without on-target off-tumor toxicity in normal tissues. However, these neoantigens are located in the intracellular region and may only be displayed as antigenic peptides on cell surfaces through MHC class I or II molecules of cancer cells after intracellular degradation, which limits their target selection for CAR design. Fortunately, this limitation can be overcome by constructing TCR-CARs through engineering TCR-like antibody, which can recognize the peptides presented by MHC molecules (pMHCs) (87). First, tumor-specific NSM is generally characterized through whole-exome sequencing (WES) and RNA-seq (88) (Figure 4). Candidate neoepitopes are then selected based on strategies such as the pVACtools algorithm that predict their binding affinity to MHC molecules (88), and immunogenicity is evaluated through cytotoxicity assay to measure their actual potency toward neoepitope-reactive T cell response (89). Next, genes that encode the neoantigen-specific TCR b-chains or their variable regions are, either collected from TCR molecules generated by stimulated T cells co-cultured with neoantigens-expressing APC, or selected from the human scFV phage library screened against the neoepitopes (87). The genes encoding variable domains of TCR (TCRv) are then linked with the intracellular domain (ICD) of CARs to produce the TCR-CAR construct. Identification of neoepitopes and development of neoantigen-specific TCR-CARs. Tumor and matched healthy tissue WES/RNA-seq is first performed to identity neoepitopes caused by NVM. Then, neoepitope pHMCs are employed for isolation of TCR-like antibodies through a phagedisplay screening. In parallel, neoantigen minigenes encoding potential neoepitopes can be designed and transfected into DCs that is co-cultured with T cells from healthy donors to obtain neoantigen-reactive T cells (89). Finally, a TCR sequence can be identified from isolated TCR-like antibodies and characterized neoantigen-reactive T cells. These TCRv genes can be used in a CAR structure to produce TCR-CAR T cells.

FIGURE 3
Combinatorial-antigen-targeted CAR. Contrary to conventional TCR T cells that may have low affinity to neoantigens and highly rely on the co-stimulation signal to be activated, TCR-CAR T cells enable independent, robust, and rapid activation (90). Recently, several neoantigenspecific TCR-CAR T cells have been constructed and validated for their anti-tumor efficacy. Walseng et al. designed two TCR-CAR-targeting neoantigens, MART-1 peptide26-35 (EAAGIGILTV) and TGFbR2 frameshift neoantigen peptide131-139 (RLSSCVPVA)30, and demonstrated their conserved specific binding ability to pMHCs (91). In another recent study, neoantigen NY-ESO-1-(SLLMWITQV) based TCR CAR T cells showed pMHC-specific induced activation and potent cytotoxicity to A375 cells loaded with NY-ESO-1 (92). Though neoantigen-based TCR-CARs can bypass the on-target toxicity occurring in TAA-based TCR-CARs, the risk for offtarget toxicity of TCRs, especially TCRs with high affinity, remains a concern. Bijen et al. suggested a peptide library scan with a screening against more cell subsets to detect off-target toxicity of TCRs will benefit the preclinical testing (93). While most ongoing CAR T cell research is focused on TAA as the target, we suggest that TCR-CAR T cells that can recognize neoepitopes have remarkable potential for personalized cancer immunotherapy, especially for tumors with a high mutational burden such as melanoma.

Antigen escape and heterogeneity
Antigen escape is a problem to long-term disease control with CAR-T cell therapy, and is considered to be the main mechanism associated with relapse in CAR T cell therapy, and has been widely observed in patients receiving CD19-CAR T cell treatment for hematological malignancies. Orlando et al. observed the loss of CD19 on the tumor cells surface through flow cytometry analysis of B-ALL cells from patients with relapsed B-ALL after CD19-targeted CAR T cell therapy, and identified the genetic mutations of the CD19 gene by sequencing of the genomes of these B-ALL cells (94). Selective pressure to mutate CD19 and outgrowth of pre-existing rare CD19-negative cells are considered as the major mechanisms of relapsed ALL cells escaping anti-CD19 CAR-T cells killing (95,96). Furthermore, antigen escape has also been reported in solid tumor treatment and may be an even more serious challenge for solid tumors due their antigen heterogeneity.
Meenakshi et al. observed that exposing U373 cells (glioblastoma cell line) with HER2 expression to HER2specific CAR T cells resulted in the emergence of HER2negtive tumor cells (97). In a phase I clinical trial targeting glioblastoma patients, the infusion of EGFRvIII CAR-T cells led to the reduction of EGFRvIII expressing glioma cells. However, tumors that survived were still widespread and retained high levels of wild-type EGFR expression (61). To address antigenic heterogeneity and prevent antigen loss, the most straightforward approach is to develop CARs that target other antigens, either by modifying individual T cells with two distinct CAR molecules (98) or by constructing CAR molecules that contain two different binding domains in tandem (99). Different from the combinatorial antigen targeted CAR T cells that require the expression of two antigens together to activate T cells, either antigen input can trigger robust anti-tumor activity in dualtargeted CAR T cells. Fry et al. developed CD22-CD19bispecific CAR T cells and demonstrated the killing effect of CD19 − CD22 + and CD19 + CD22 − B-ALL cell lines in vitro, as well as the significant B-ALL clearance in an NSG mouse model (99). Similarly, Choi et al. developed a bicistronic construct to drive expression of a EGFRvIII-specific CAR and a bispecific T cell engager (BiTE) against EGFR (61) based on their previous finding of viable tumors with wild-type EGFR expression, and showed their specific antitumor activity against heterogeneous solid tumors (100) ( Figure 5A).
In addition, the quest for a split universal programmable (SUPRA) CAR system that can integrate signals from multiple antigens has recently become a flashpoint in CAR T cell therapy. A SUPRA CAR system is composed of a zipCAR that has a leucine zipper as the extracellular portion of the CAR and zipFv that has a scFv fused to a cognate leucine zipper that can bind to the leucine zipper on the zipCAR (101) ( Figure 5B). Therefore, it can use different zipFvs to target multiple tumor antigens for the treatment of heterogeneous tumors and relapsed tumors with escaped antigens. Besides that, a SUPRA CAR system can finely tune T cell activation strength to mitigate over-activation by adjusting zipper affinity and zipFvs infusion levels. Thus we suppose that zipTCRv which targets numerous distinct neoantigens can be designed by combination of zipCAR construct design with neoantigen-specific TCR-CAR. Cytotoxic T cells with enhanced anti-tumor activity can then be redirected to tumor cells immediately after the infusion of zipTCRv, which may be useful in combatting relapse in solid tumors without re-engineering T cells.

Trafficking obstacles
Unlike hematologic malignancies, CAR T cells must successfully target and infiltrate solid tumors, which depends on successful trafficking of the T cells from the blood into the solid tumor sites. Thus, local delivery of CAR T cells is now widely explored. Tchou et al. detected CAR mRNA in both peripheral blood and injected tumor tissues after intratumoral injection of mRNA c-Met-CAR T cells to c-Met-expressing breast cancer patients. They suggested that intratumoral injection were well tolerated and induced a detectable inflammatory response within tumors (102). Though intratumoral injection of CAR T cells can bypass trafficking obstacles and has been considered in several pre-clinical tests, it is unlikely to achieve systemic function under metastatic conditions (103, 104). The trafficking of immune cells generally depends on the matching between the chemokine receptors on the surface of the immune cells and the chemokines secreted by target cells, and adhesion receptors on both cells. Besides, CAR T cell trafficking is also impacted by the disorganized and uncoordinated expression of chemokines and their receptors within the TME.
CXCR3 is one kind of chemokine receptor, which is primarily expressed by T lymphocytes after T cell activation and is considered to be one of the most primal chemokine receptors on the surface of CAR T cells (105). Unfortunately, the mismatches of chemokines to their receptors, with the downregulated expression level of CXCR3 ligands in the TME in many cancers probably make CXCR3 high CAR T cells unable to effectively target tumor sites (106). To address this problem, CAR T cells that co-express better-matched chemokine receptors have recently been designed. Wang et al. constructed a mesothelin-specific CAR co-expressing cell chemokine receptors CCR2b and CCR4, and proved by trans-well assay that both CCR2b and CCR4 enhanced the migration of mesothelin-specific CAR T cells (107). Lin et al. also demonstrated greater anti-tumor activity of CCR2b-expressing T cells and increased infiltrated T cell numbers in a breast cancer model (108). The increased infiltration ability of chemokineexpressing T cells also addressed another significant physical obstacle during CAR-T cells trafficking, the blood-brain barrier (BBB). Recent research by Li et al. suggested that co-expression of CCR2b in B7-H3.CAR-T cells can improve migration toward CCL2 and the capability of passing BBB, providing enhanced antitumor activity against brain tumor lesions. They also proved the comparable antitumor activity of such CCR2b-B7-H3.CAR-T cells by co-culturing with NSCLC cell lines in vitro.
Additionally, in A549 and H520 cancer brain co-xenograft tumor models, CCR2b co-expressing CAR-T cells showed superior antitumor activity through higher accumulation in the head region (109).
Moreover, as a kind of virus that specifically infects the tumor cells naturally, oncolytic viruses combined with chemotactic chemokines and cytokines both exhibited the potential to attract CAR T cells to tumor sites. In particular, IFNg-mediated CXCL-9/10 secretion has been found to play a critical role in T cell trafficking within the TME (110). Based on the natural ability of oncolytic viruses to improve CXCL-9/10 expression levels locally within the TME, Fu et al. employed oncolytic viruses with adoptive T cells in pre-clinical studies and demonstrated that they facilitated T cell migration and persistence, leading to a significantly enhanced therapeutic effect (111). Arming oncolytic viruses with chemokine or cytokine ligands was considered to be an effective method to exploit their ability to reverse the inefficient trafficking of cytotoxic T cells.
Recently, Nishio et al. combined CAR T cells with an oncolytic virus armed with the chemokine RANTES and the cytokine IL15 in a neuroblastoma mouse model, and found that the intratumoral release of both RANTES and IL15 attracted CAR-T cells to improve CAR T cell influx (112). Moreover, the delivery of cytokines supporting APCs through oncolytic viruses may recruit DCs and modulate the cytokine milieu to facilitate an adaptive immune response (activated DCs can secrete CXCL-9/10), thus benefitting the CAR T cell trafficking, activation, and proliferation within the TME (113). Despite the fact that there are numerous potential strategies to combine oncolytic viruses and CAR T cell therapy, the complexity of oncolytic viruses and cellular interaction A B FIGURE 5 Schematic of CART.BiTE and SUPRA CAR. (A) Gene-modified EGFRvIII-CAR T cells deliver bispecific antibodies known as BiTEs6 that are combined with antibody against wild-type EGFR (aEGFR) and antibody against the CD3 signal domain (aCD3). Therefore, CART.BiTE cells obtain the capacity to target EGFRvIII-negative tumor cells. (B) A SUPRA CAR system is composed of a zipCAR and zipFv. A leucine zipper (BZip) serves as the extracellular portion of the CAR. A cognate leucine zipper that can bind to the BZip links with the scFv region.
within the TME may lead to several unforeseen effects. For example, Ding et al. indicated that a certain isoform of chemokine receptor appears to drive tumor invasion in several types of cancers (114,115), and Korniejewska et al. further suggested that the interaction of CXCR3-A (expressed on tumor cells) with CXCL-9 promotes tumor metastasis through activation of the phosphatidylinostol 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways. Due to the interaction of CXCR3-B, endothelial cell proliferation is downregulated, and tumor angiogenesis is depressed (116). Therefore, the complicated network between chemokines and their receptors in different immune cells puts forward further challenges for employing chemokine-armed oncolytic viruses with CAR T cells. Apart from chemokine co-expression and oncolytic viruses, the rise of nanotechnology may also facilitate novel trafficking strategies. Nanomaterials have already been widely employed in many CAR T cell therapy pre-clinical trials, mainly for controlling the co-delivery of drugs and enable long-term retention with sustained exposure. Grosskopf et al. recently engineered a novel CAR T cell delivery platform based on Polymer-Nanoparticle hydrogels that induced a transient inflammatory niche for CAR-T cell expansion and activation in a mouse model, and provided a feasible treatment for metastases based on comparable efficacy during distal administration (117). Another character of nanoparticles that has not been fully explored when combining them with CAR T cell therapy is their modifiable surfaces. The modifiable surfaces and physicochemical features of nanomaterials also enable the specific trafficking of nanomaterial-based drugs, which has led to the recent production of several nanomaterial-based vaccines with target-specific trafficking abilities (118). The success of nanomaterial-based vaccine trafficking implies the potential for specifically trafficking of CAR T cells to the tumor sites of solid tumors in the future. However, there are still obstacles that need to be overcome in constructing nanomaterial-based T cell therapies, such as the toxicity caused by the oxidation and DNA destruction capacity of the nanomaterials (119). These obstacles, together with the concerns about the toxicity and applicability, make nanomaterial-based T cell therapies still far from being applied in the nowdays clinical trials.

Immunosuppressive TME
The TME presents additional barriers to the successful application of CAR T cell therapy to solid tumors. The immunosuppressive TME contains multiple components, including physical, metabolic, and immunological barriers. Physical barriers are generated by stroma such as the carcinoma-associated fibroblasts, collagens, vascular beds, and dense extracellular matrix (ECM) with high tissue pressure to prevent extravasation (120). Genetically reprogrammed CAR T cells that secret enzymes, such as heparanase or hyaluronidase, that degrade ECM showed enhanced T cell penetration and better elimination of tumor cells (121). Another novel method of removing ECM involves the use of nanomaterials. Chen et al. encapsulated a photothermal agent, indocyanine green, into a PLGA nanomaterial and injected the encapsulated nanoparticle intratumorally at mice model. Subsequent near-infrared light irradiation allowed the photothermal agent to generate heat in the tumor site for the disruption of ECM before CAR T cell administration (122). Beside the enriched ECM, metabolic barriers such as hypoxia environment and lactate-induced acidosis, which are the consequence of excessive glycolysis of tumor cells, contribute to tumor genomic changes and metabolic dysfunction of immunogenic T cells (123). Interestingly, hypoxia environment can be employed by researchers as the selective sensor for CAR T cell activation. Kosti et al. proposed a rigorous hypoxia-sensing CAR T cell system that achieves selective expression of a pan-ErbB-targeted CAR molecules within the TME in solid tumor characterized by the hypoxia environment, achieving a considerable anti-tumor efficacy without off-tumor toxicity (124). To overcome such metabolic barriers, combination therapies such as applying hypoxia inducible factor antagonists with CAR T cells deserve consideration and further exploration.
Suppressive immune cells and cytokines also play the central role as the immunological barriers in mediating immune tolerance in tumor tissue. One promising strategy is to redirect or circumvent suppressive immune cells and cytokines. Transforming growth factor b (TGFb) is one of the most important inhibitory tumor cytokines, which promotes epithelial-to-mesenchymal transition, could enhance ECM production, and directly suppress T cell effector functions (125). Several approaches have been developed to counteract the function of TGFb in recent CAR T cell therapy studies. For example, the transduction of a dominant-negative TGFb receptor (TGFbR) (126) or CRIPSR-Cas9-mediated knockout of the TGFbRII (127) has been found to induce increased efficacy and the central memory phenotype, as well as less exhaustion in xenograft solid tumor models.
Alternatively, it has been found that the secretion of proinflammatory soluble factors/cytokines through engineered CAR T cells or nanomaterials can increase the CAR T cells response and inhibit suppressor cells in the TME. Armored CAR constructs that overexpress cytokines such as IL-7, IL-12, and IL-18 have been shown to be able to activate more proinflammatory endogenous immune cells and exhibit enhanced anti-tumor response (128)(129)(130). Zhang et al. built lipid nanoparticles coated with the tumor-targeting peptide iRGD, and loaded with a combination of a PI3K inhibitor P-3065 and an a-GalCer agonist for therapeutic T cells, in order to transform the TME from suppressive to stimulatory state. In a mouse model of breast cancer, this lipid nanoparticle complex provided a two-week window for CAR T cells to home in on the lesion, undergo robust expansion, and trigger tumor regression (131).
Furthermore, combining CAR T cell therapy and ICB holds promise for counteracting the immunosuppressive TME and has been explored in several studies. This can be performed by cellextrinsic strategies, in which ICB and CAR T cells are administered separately. Gargett et al. showed that the use of PD-1 blockade pembrolizumab together with GD2-CAR T cells enhanced T cell survival, and promoted killing activity in PD-L1 + tumor cell lines (132). The technique can also be performed using cell-intrinsic strategies, in which edited CAR T cells are employed alone without relying on repeated dosing of ICB.

Future research
Despite CAR T cell therapy achieving remarkable outcomes and rapid development, many challenges discussed above have contributed to its limited success in solid tumors. These challenges must be overcome in order to get durable clinical benefits and maximize survival. Currently, driven by the interconnected feedback loops between clinical trials and labbased research, CAR designs have shifted from simple permutations of co-stimulatory domains and scFv to more sophisticated strategies. For example, SUPRA CAR were developed to control CAR T cell activation remotely and CART.BiTE was designed to prevent off-tumor toxicity and antigen escape (135). Neoantigen-specific TCR-like CAR T cell therapy was proposed as a novel method to solve the biggest challenge in solid tumor T cell therapy, the on-target off-tumor toxicity from TAAs. Apart from neoantigen-CAR, further understanding about mechanisms in the TME and immune cells subpopulations, together with improved development of genetic approaches, are leading the way forward for increasing the efficacy of CAR T cell therapy in solid tumors.

CRISPR screens and genetic modification
With improved understanding of key factors of intrinsic resistance mechanisms within TME, novel strategies targeting these factors using gene-editing and engineering approaches have been designed to enhance CAR T cell efficacy to clear out tumor cells and quash persistence within TME. The outsourced ex vivo designs and manufacture process of CAR T cells, different from other traditional drugs, also make it possible to modify the CAR T cells directly using genetic tools such as the CRISPR/Cas9 system. Besides the CRISPR/Cas9-mediated PD-1 knock out discussed above, Giuffrida et al. have indicated that targeting adenosine A 2A receptors with a clinically relevant CRISPR/Cas strategy can significantly increase the number of infiltrating CAR T cell and their ability to inhibit tumor growth. They hypothesized that this was driven by downregulated adenosine-mediated transcriptional pathways to enhance the production of IFNg (136).
The indispensable function of IFNg in CAR T cell therapy targeting solid tumors has also been demonstrated by Larson et al, who conducted a genome-wide CRISPR knockout screen in glioblastoma and found that the knout out of genes in the IFNg receptor signaling pathway (e. g., IFNGR1, JAK1, and JAK2) made glioblastoma cells more resistant to CAR T cells both in vitro and in vivo (137). Such genome-wide systematic CRISPR screens may shift the CAR engineering from blindly focusing on individual features to combinations of multiple gene modifications with predicted benefits. Shifrut et al. and Legut et al. respectively performed a CRISPR/Cas9-based genomescale screening, and identified negative regulators and synthetic drivers of T cell proliferation following stimulation by comparing the gene enrichment by barcode number after stimulation and incubation (54, 138). In addition, Ye et al. developed a dead-guide RNA-based genome scale gain-offunction CRISPR/Cas9 screen and identified PRODH2 as one of the key enzymes for reprogramming the proline metabolism in CAR-T cells, leading to enhanced antitumor efficacy (139). To conclude, CRISPR/Cas9 technology, especially genome-wide screens based on it, has accelerated the development of nextgeneration CAR-T cells and put forward exciting new directions for the design of therapeutic gene modification.

Progenitor-like T cells
While current manufacturing efforts for adoptive cell therapy generally use CD4 + /CD8 + T cell separation or just heterogeneous T cells obtained from certain patients, there is evidence to suggest that some subsets of T cells may be more efficacious as the source of CAR-T cells. However, it's still unclear in which subpopulation of T cells the endowment of CAR will be most effective in treating certain cancers. Recently, several studies have identified that the less differentiated progenitor-like T cell subsets have a greater proliferative capacity (such as T memory stem cells (T SCM ) and naïve T cells (T N )), which is a promising strategy to prolong the persistence of adoptive T cells and sustain remission (140). Based on a thorough paired analysis from high-dimensional flow cytometry, exome, single cell, and RNA sequencing, Ghorani et al. described the T cell differential landscape in TME and showed that gene feature redistribution from the progenitor-like state to differentiated dysfunctional states was highly associated with the unsatisfied prognosis of NSCLC (141).
Biasco et al. also demonstrated this finding in CAR T cell therapy clinically. They found that T SCM instead of effector T cells became more prevalent over time with long-term maintenance of CAR T cell clones, suggesting the critical role of T SCM cells, which account for only a small fraction in the infused product (142). Therefore, strategies to enhance the abundance or activity of the progenitor-like T cell pool in infused products may lead to therapeutic advantages. Nevertheless, the antitumor response potential of these T cell subpopulations after CAR engineering has not been fully explored, and require subset purification, CAR engineering, and validation. However, due to the limited sorting capacity and scalability of the current cell purification platforms, as well as the relative scarcity of circulating progenitor-T cells, the purification and enrichment of progenitor-T cells from PBMC samples has become the biggest manufacturing bottleneck impeding scale-up and scale-out efforts of this process (143).
An alternative method to produce progenitor-T cells that bypasses these limitations is to directly derive progenitor-T cells from hematopoietic stem and progenitor cells (HSPCs) or even from human pluripotent stem cells (hPSCs). Recently, Shukla et al. and Trotman et al. have designed the fully defined serumfree cell-free system, in which CD7+ progenitor-T cells can be differentiated from mouse or human HSPCs (144,145). We proposed that a defined and scalable progenitor-T cell differentiation platform from hPSCs can be designed and further expanded by combining it with single cell sequencing to explore the evolutionary landscape of T cells and to identify the molecular switches for each T cell subpopulation.

Conclusion
The tremendous success of CAR T cells in treating hematologic malignancies has led to increased commercial approvals in recent years. Now, the gradually-revealed toxicity and relapse potential of these treatments, together with their failure in solid tumors have sent researchers back to the proverbial drawing board. A better understanding of the mechanisms of efficacy, resistance, and solid tumor barriers has driven advances in both CAR engineering and clinical trial design. The novel delivery technologies such as cytokines encapsulated nanomaterials and cell warehouse have advanced the state of the art to overcome TME beyond the traditional methods. Innovations in CAR design like SUPRA CAR may very well lead to improved responses and may transform the treatment of solid tumors. Finally, we suggested that combining CAR T cell treatments with novel scRNA sequencing, CRISPR/Cas9-based screening and modification technology, neoantigen based TCR-CAR design, and CAR T cells driven from progenitor-like T cells may provide abundant potential treatment strategies for solid tumors and opportunities for additional improvements in the future.

Author contributions
ZZ, YZ and AC was responsible for project design and writing of the manuscript, CT, JL and JT responsible for review, and editing. All authors contributed to the article and approved the submitted version. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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